2026-07-23T08:35:19Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:19041 2024-04-24T08:33:41Z ddc:004 open_access

Coupling CP with Deep Learning for Molecular Design and SARS-CoV2 Variants Exploration (Invited Talk) Schiex, Thomas graphical models deep learning constraint programming cost function networks random Markov fields decision-focused learning protein design The use of discrete optimization, including Constraint Programming, for designing objects that we completely understand is quite usual. In this talk, I'll show how designing specific biomolecules (proteins) raises new challenges, requiring solving problems that combine precise design targets, approximate laws, and design rules that can be deep-learned from data. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Thomas Schiex 2023 Is Part Of LIPIcs, Volume 280, 29th International Conference on Principles and Practice of Constraint Programming (CP 2023) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.CP.2023.4 urn:nbn:de:0030-drops-190415 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.4 eng https://creativecommons.org/licenses/by/4.0/legalcode